Metabolic reprogramming in Rheumatoid Arthritis Synovial Fibroblasts: A hybrid modeling approach

13C Metabolic Flux Analysis in Chondrocytes Reveals a Novel Switch in Metabolic Phenotype

Chondrocytes are typically known for their anaerobic metabolism both in vivo and under culture conditions in vitro. However, chondrocytes have been shown to display greater biosynthetic activity when subjected to conditions that elicit aerobic metabolism. We have previously shown that tissue formation by chondrocytes can be upregulated by controlling nutrient availability and that this response arises from changes in glucose metabolism. The aim of the present study was to further characterize these changes through 13C-metabolic flux analysis (13C-MFA), as well as to determine the most optimal response. Primary bovine chondrocytes were grown in scaffold-free high-density tissue culture. [U-13C] glucose labeling experiments were combined with a tissue-specific metabolic network model to carry out 13C-MFA under varying levels of nutrient availability. 13C-MFA results demonstrated that when subjected to increasing nutrient availability, chondrocytes switch from a predominately anaerobic to a mixed aerobic-anaerobic phenotype. This metabolic switch was attributed to the saturation of the lactate fermentation pathway and metabolite overflow toward the tricarboxylic acid cycle. This effect appears to be similar to, but the inverse of, the Crabtree effect ("inverse Crabtree effect"). The relationships between metabolic flux and nutrient availability were then utilized to identify culture conditions that promote enhanced tissue formation. This novel metabolic effect presents a simple but effective approach for enhancing the biosynthetic response of chondrocytes-a key requirement to develop functional engineered cartilaginous tissue for joint resurfacing.

MetaLo: metabolic analysis of Logical models extracted from molecular interaction maps

Molecular interaction maps (MIMs) are static graphical representations depicting complex biochemical networks that can be formalized using one of the Systems Biology Graphical Notation languages. Regardless of their extensive coverage of various biological processes, they are limited in terms of dynamic insights. However, MIMs can serve as templates for developing dynamic computational models. We present MetaLo, an open-source Python package that enables the coupling of Boolean models inferred from process description MIMs with generic core metabolic networks. MetaLo provides a framework to study the impact of signaling cascades, gene regulation processes, and metabolic flux distribution of central energy production pathways. MetaLo computes the Boolean model's asynchronous asymptotic behavior, through the identification of trap-spaces, and extracts metabolic constraints to contextualize the generic metabolic network. MetaLo is able to handle large-scale Boolean models and genome-scale metabolic models without requiring kinetic information or manual tuning. The framework behind MetaLo enables in depth analysis of the regulatory model, and may allow tackling a lack of omics data in poorly addressed biological fields to contextualize generic metabolic networks along with improper automatic reconstructions of cell- and/or disease-specific metabolic networks. MetaLo is available at https://pypi.org/project/metalo/ under the terms of the GNU General Public License v3.

Reversing pathological cell states: the road less travelled can extend the therapeutic horizon

Acquisition of omics data advances at a formidable pace. Yet, our ability to utilize these data to control cell phenotypes and design interventions that reverse pathological states lags behind. Here, we posit that cell states are determined by core networks that control cell-wide networks. To steer cell fate decisions, core networks connecting genotype to phenotype must be reconstructed and understood. A recent method, cell state transition assessment and regulation (cSTAR), applies perturbation biology to quantify causal connections and mechanistically models how core networks influence cell phenotypes. cSTAR models are akin to digital cell twins enabling us to purposefully convert pathological states back to physiologically normal states. While this capability has a range of applications, here we discuss reverting oncogenic transformation.

The therapeutic effects of gingival mesenchymal stem cells and their exosomes in a chimeric model of rheumatoid arthritis

BACKGROUND

Rheumatoid arthritis is a chronic systemic autoimmune disease that involves transformation of the lining of synovial joints into an invasive and destructive tissue. Synovial fibroblasts become transformed, invading and destroying the bone and cartilage of the affected joint(s). Due to the significant role these cells play in the progression of the disease process, developing a therapeutic strategy to target and inhibit their invasive destructive nature could help patients who are afflicted with this debilitating disease. Gingival-derived mesenchymal stem cells are known to possess immunomodulatory properties and have been studied extensively as potential cell-based therapeutics for several autoimmune disorders.

METHODS

A chimeric human/mouse model of synovitis was created by surgically implanting SCID mice with a piece of human articular cartilage surrounded by RASF. Mice were injected once with either GMSC or GMSCExo at 5-7 days post-implantation. Histology and IHC were used to assess RASF invasion of the cartilage. Flow cytometry was used to understand the homing ability of GMSC in vivo and the incidence of apoptosis of RASF in vitro.

RESULTS

We demonstrate that both GMSC and GMSCExo are potent inhibitors of the deleterious effects of RASF. Both treatments were effective in inhibiting the invasive destructive properties of RASF as well as the potential for these cells to migrate to secondary locations and attack the cartilage. GMSC home to the site of the implant and induce programmed cell death of the RASF.

CONCLUSIONS

Our results indicate that both GMSC and GMSCExo can block the pathological effects of RASF in this chimeric model of RA. A single dose of either GMSC or GMSCExo can inhibit the deleterious effects of RASF. These treatments can also block the invasive migration of the RASF, suggesting that they can inhibit the spread of RA to other joints. Because the gingival tissue is harvested with little difficulty, relatively small amounts of tissue are required to expand the cells, the simple in vitro expansion process, and the increasing technological advances in the production of therapeutic exosomes, we believe that GMSCExo are excellent candidates as a potential therapeutic for RA.

Dexamethasone inhibits IL-8 via glycolysis and mitochondria-related pathway to regulate inflammatory pain

BACKGROUND

Dexamethasone (Dexa) has been recently found to exert an analgesic effect, whose action is closely related to IL-8. However, whether dexamethasone induces antinociception via glycolysis and mitochondria-related pathways is still unclear.

METHODS

Right hind paw inflammatory pain in mice was induced by intraplantar injection of Freund's Complete Adjuvant (FCA). Von Frey test was then used to measure the paw withdrawal threshold. The detection of glycolysis and mitochondrial pathway-related proteins and IL-8 were determined by Western blot and ELISA. The potential interaction between Dexa and fructose-1,6-bisphosphate (FBP, a PKM2 activator) was examined by simulation predictions using molecular docking.

RESULTS

Intrathecal administration of Dexa (20 µg/20 µL) had an obvious analgesic effect in FCA-treated mice, which was counteracted by the glycolysis inhibitor 2-deoxyglucose (2-DG, 5 mg/20 µL) or the mitochondria-related pathway inhibitor oligomycin complex (Oligo, 5 µg/20 µL). In the glycolysis pathway, Dexa decreased GLUT3 and had no impact on HIF-1α expression during FCA-induced inflammation. Additionally, Dexa further increased the PKM2 level, accompanied by the formation of hydrogen bonds between Dexa and the PKM2 activator fructose-1,6-bisphosphate (FBP). In the mitochondrial pathway, Dexa downregulated the expression of Mfn2 protein but not the PGC-1α and SIRT-1 levels in the spinal cord. Moreover, both 2-DG and Oligo decreased Mfn2 expression. Finally, IL-8 level was reduced by the single or combined administration of Dexa, 2-DG, and Oligo.

CONCLUSION

Dexa attenuated IL-8 expression via glycolysis and mitochondrial pathway-related proteins, thus mediating the analgesic effect during inflammatory pain.

Hybrid computational modeling highlights reverse warburg effect in breast cancer-associated fibroblasts

Cancer-associated fibroblasts (CAFs) are amongst the key players of the tumor microenvironment (TME) and are involved in cancer initiation, progression, and resistance to therapy. They exhibit aggressive phenotypes affecting extracellular matrix remodeling, angiogenesis, immune system modulation, tumor growth, and proliferation. CAFs phenotypic changes appear to be associated with metabolic alterations, notably a reverse Warburg effect that may drive fibroblasts transformation. However, its precise molecular mechanisms and regulatory drivers are still under investigation. Deciphering the reverse Warburg effect in breast CAFs may contribute to a better understanding of the interplay between TME and tumor cells, leading to new treatment strategies. In this regard, dynamic modeling approaches able to span multiple biological layers are essential to capture the emergent properties of various biological entities when complex and intertwined pathways are involved. This work presents the first hybrid large-scale computational model for breast CAFs covering major cellular signaling, gene regulation, and metabolic processes. It was generated by combining a cell- and disease-specific asynchronous Boolean model with a generic core metabolic network leveraging both data-driven and manual curation approaches. This model reproduces the experimentally observed reverse Warburg effect in breast CAFs and further identifies Hypoxia-Inducible Factor 1 (HIF-1) as its key molecular driver. Targeting HIF-1 as part of a TME-centered therapeutic strategy may prove beneficial in the treatment of breast cancer by addressing the reverse Warburg effect. Such findings in CAFs, in light of our previously published results in rheumatoid arthritis synovial fibroblasts, point to a common HIF-1-driven metabolic reprogramming of fibroblasts in breast cancer and rheumatoid arthritis.

A large-scale Boolean model of the rheumatoid arthritis fibroblast-like synoviocytes predicts drug synergies in the arthritic joint

Rheumatoid arthritis (RA) is a complex autoimmune disease with an unknown aetiology. However, rheumatoid arthritis fibroblast-like synoviocytes (RA-FLS) play a significant role in initiating and perpetuating destructive joint inflammation by expressing immuno-modulating cytokines, adhesion molecules, and matrix remodelling enzymes. In addition, RA-FLS are primary drivers of inflammation, displaying high proliferative rates and an apoptosis-resistant phenotype. Thus, RA-FLS-directed therapies could become a complementary approach to immune-directed therapies by predicting the optimal conditions that would favour RA-FLS apoptosis, limit inflammation, slow the proliferation rate and minimise bone erosion and cartilage destruction. In this paper, we present a large-scale Boolean model for RA-FLS that consists of five submodels focusing on apoptosis, cell proliferation, matrix degradation, bone erosion and inflammation. The five-phenotype-specific submodels can be simulated independently or as a global model. In silico simulations and perturbations reproduced the expected biological behaviour of the system under defined initial conditions and input values. The model was then used to mimic the effect of mono or combined therapeutic treatments and predict novel targets and drug candidates through drug repurposing analysis.

Therapeutic Effects of Gingival Mesenchymal Stem Cells and Their Exosomes in a Chimeric Model of Rheumatoid Arthritis

Background

Rheumatoid arthritis is a chronic systemic autoimmune disease that involves transformation of the lining of synovial joints into an invasive and destructive tissue. Synovial fibroblasts become transformed, invading and destroying bone and cartilage of the affected joint(s). Due to the significant role these cells play in the progression of the disease process, developing a therapeutic strategy to target and inhibit their invasive destructive nature could help patients who are affiicted with this debilitating disease. Gingival-derived mesenchymal stem cells are known to possess immunomodulatory properties and have been studied extensively as potential cell-based therapeutics for several autoimmune disorders.

Methods

A chimeric human/mouse model of synovitis was created by surgically implanting SCID mice with a piece of human articular cartilage surrounded by RASF. Mice were injected once with either GMSC or GMSCExo at 5-7 days post-implantation. Histology and IHC were used to assess RASF invasion of the cartilage. Flow cytometry was used to understand the homing ability of GMSC in vivo and the incidence of apoptosis of RASF in vitro.

Results

We demonstrate that both GMSC and GMSCExo are potent inhibitors of the deleterious effects of RASF. Both treatments were effective in inhibiting the invasive destructive properties of RASF as well as the potential of these cells to migrate to secondary locations and attack the cartilage. GMSC home to the site of the implant and induce programmed cell death of the RASF.

Conclusions

Our results indicate that both GMSC and GMSCExo can block the pathological effects of RASF in this chimeric model of RA. A single dose of either GMSC or GMSCExo can inhibit the deleterious effects of RASF. These treatments can also block the invasive migration of the RASF, suggesting that they can inhibit the spread of RA to other joints. Because the gingival tissue is harvested with little difficulty, relatively small amounts of tissue are required to expand the cells, the simple in vitro expansion process, and the increasing technological advances in the production of therapeutic exosomes, we believe that GMSCExo are excellent candidates as a potential therapeutic for RA.

A guide for developing comprehensive systems biology maps of disease mechanisms: planning, construction and maintenance

As a conceptual model of disease mechanisms, a disease map integrates available knowledge and is applied for data interpretation, predictions and hypothesis generation. It is possible to model disease mechanisms on different levels of granularity and adjust the approach to the goals of a particular project. This rich environment together with requirements for high-quality network reconstruction makes it challenging for new curators and groups to be quickly introduced to the development methods. In this review, we offer a step-by-step guide for developing a disease map within its mainstream pipeline that involves using the CellDesigner tool for creating and editing diagrams and the MINERVA Platform for online visualisation and exploration. We also describe how the Neo4j graph database environment can be used for managing and querying efficiently such a resource. For assessing the interoperability and reproducibility we apply FAIR principles.